This study provides the following normative values for photo-oculography in healthy children aged 6 weeks through 6 years of age: attention time, smooth pursuit time, and gain for three stimulus velocities presented horizontally and vertically. This normative database should help to diagnose pathologic ophthalmological or neuropediatric conditions, to perform screening interventions, and to initiate therapies.
Background: Optokinetic nystagmus (OKN) gain is asymmetrical between temporal to nasal (TN) and nasal to temporal (NT) stimulation in infancy and decreases at older ages. The age at which OKN gain becomes symmetrical and decreases is debated. The aim was to investigate OKN over the whole lifespan in a large sample of healthy subjects. Methods: In a prospective, cross sectional study OKN was tested monocularly using TN and NT small field stimulation. Stimulation velocity was 15˚/s and 30˚/s for children aged under 1 year (n = 97), and 15˚/s, 30˚/s, 45˚/s, and 60˚/s for older subjects (1-9 years, n = 66; 10-89 years, n = 86). Gain was measured using infrared oculography. Results: Significant OKN gain asymmetry in favour of TN versus NT stimulation was found during the first 5 months of life (p,0.05). Only at 11 months of age was OKN symmetrical in 100% of the subjects. The percentage of children with symmetrical OKN decreased with increasing stimulus velocity. OKN gain increased in the second and third years (p,0.05 for 15˚/s), remained stable until 50 years of age, and showed a small but significant decrease afterwards for the tested velocities (between 6% and 18%, p,0.05). Conclusions: Infrared oculography is an accurate method to assess OKN, especially in children. Knowledge about change of OKN in healthy subjects could be helpful to interpret OKN in patients with abnormal binocular vision or lesions of the central nervous system.
Objective: To present a quick algorithm to automatically analyze the raw data acquired by a photo-oculography (POG) system. Methods: We developed a simple algorithm for POG data analysis based on an extrapolation of missing values due to blinking and on exclusion of outliers using the robust mean and standard deviation. Results: POG curves of 4 children aged between 1.5 and 7 years are shown before and after automatic analysis. After applying our algorithm, the curves are much smoother. Conclusion: Our algorithm allows a quick data analysis and will help to better interpret and analyze POG data.
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